---
base_model: unsloth/meta-llama-3.1-8b-instruct-bnb-4bit
library_name: peft
license: llama3.1
tags:
- trl
- sft
- unsloth
- generated_from_trainer
model-index:
- name: meta-llama-Meta-Llama-3.1-8B-Instruct_SFT_E1_D20001
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nicola-er-ho/clembench-playpen-sft/runs/vk1p42l3)
# meta-llama-Meta-Llama-3.1-8B-Instruct_SFT_E1_D20001

This model is a fine-tuned version of [unsloth/meta-llama-3.1-8b-instruct-bnb-4bit](https://huggingface.co/unsloth/meta-llama-3.1-8b-instruct-bnb-4bit) on the None dataset.

## Model description

The Model is trained only on successful episodes produced by the top 10 models from the clembench benchmark version 0.9 and 1.0. The success was measured in terms of most overall
successful episodes across all games.

| Place | Item |
|-------|------|
| 1 | gpt-4-0613-t0.0--gpt-4-0613-t0.0 |
| 2 | claude-v1.3-t0.0--claude-v1.3-t0.0 |
| 3 | gpt-4-1106-preview-t0.0--gpt-4-1106-preview-t0.0 |
| 4 | gpt-4-t0.0--gpt-4-t0.0 |
| 5 | gpt-4-0314-t0.0--gpt-4-0314-t0.0 |
| 6 | claude-2.1-t0.0--claude-2.1-t0.0 |
| 7 | gpt-4-t0.0--gpt-3.5-turbo-t0.0 |
| 8 | claude-2-t0.0--claude-2-t0.0 |
| 9 | gpt-3.5-turbo-1106-t0.0--gpt-3.5-turbo-1106-t0.0 |
| 10 | gpt-3.5-turbo-0613-t0.0--gpt-3.5-turbo-0613-t0.0 |

## Intended uses & limitations

More information needed

## Training and evaluation data

Traning Data: D20001

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 7331
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 5
- num_epochs: 1

### Training results



### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1